Metabolomics fingerprint of three Clematis L. species by UPLC-MS/MS for geographical and varietal classification
Bibliographic record
Abstract
Clematis L. is a genus with global distribution and significant usage in traditional Chinese medicine. Traditionally, species authentication for Clematis L. has relied on morphological characteristics, but such method is susceptible to errors and lacks reproducibility. In this study, an untargeted UPLC-MS/MS-based metabolomics approach was employed to comprehensively discriminate Clematis tangutica (Maxim.) Korsh, C. intricata and Clematidis Radix et Rhizoma (CRR) from eight provinces in China. 2331 differential metabolites were identified by principal components analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA), which revealed distinct separations among the studied regions. The KEGG metabolic pathway analysis showed that flavone and flavonol biosynthesis and flavonoid biosynthesis were closely associated with geographical origin. This work established the metabolomics evidence that flavonoid biosynthesis serves as a biochemical signature of geographical adaptation in Clematis, providing a scientific foundation for precise origin traceability, resource conservation, and quality standardization of medicinal species in traditional Chinese medicine.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".